DBMS > EJDB vs. GridGain vs. Neo4j vs. TempoIQ

System Properties Comparison EJDB vs. GridGain vs. Neo4j vs. TempoIQ

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

GridGain is an in-memory computing platform, built on Apache Ignite

Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Primary database model

Document store

Columnar
Key-value store
Object oriented DBMS
Relational DBMS

Graph DBMS

Time Series DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.13
Rank	#331	Overall
	#46	Document stores

Score	1.48
Rank	#150	Overall
	#1	Columnar
	#26	Key-value stores
	#2	Object oriented DBMS
	#69	Relational DBMS

Score	42.68
Rank	#21	Overall
	#1	Graph DBMS

Website

github.com/Softmotions/ejdb

www.gridgain.com

neo4j.com

tempoiq.com (offline)

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

www.gridgain.com/docs/index.html

neo4j.com/docs

Developer

Softmotions

GridGain Systems, Inc.

Neo4j, Inc.

TempoIQ

Initial release

2012

2007

2012

Current release

GridGain 8.5.1

5.23, August 2024

License

Commercial or Open Source

Open Source

GPLv2

commercial, open source

Open Source

GPL version3, commercial licenses available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.

Implementation language

Java, C++, .Net, Python, REST, SQL

Java, Scala

Server operating systems

server-less

Linux
OS X
Solaris
Windows
z/OS

Linux

Can also be used server-less as embedded Java database.
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-free and schema-optional

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

pluggable indexing subsystem, by default Apache Lucene

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

APIs and other access methods

in-process shared library

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3

HTTP API

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

yes

User defined Procedures and Functions

Triggers

yes (cache interceptors and events)

yes

via event handler

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes using Neo4j Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes (replicated cache)

Causal Clustering using Raft protocol

available in in Enterprise Version only

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Causal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Relationships in graphs

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Role-based access control
Security Hooks for custom implementations

Users, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)

simple authentication-based access control

More information provided by the system vendor

Specific characteristics

Neo4j delivers graph technology that has been battle tested for performance and scale...
» more

Competitive advantages

Neo4j is the market leader, graph database category creator, and the most widely...
» more

Typical application scenarios

Real-Time Recommendations Master Data Management Identity and Access Management Network...
» more

Key customers

Over 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
» more

Market metrics

Neo4j boasts the world's largest graph database ecosystem with more than 140 million...
» more

Licensing and pricing models

GPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
» more

News

The Ethics of Generative AI: Understanding the Principles and Risks
18 September 2024

GraphSummit Europe 2024: Actionable Insights From Industry Leaders and Innovators
18 September 2024

This Week in Neo4j: Knowledge Graph, Data Loading, Olympics, CSV and more
7 September 2024

Neo4j Expands Cloud Database Capabilities to Power Enterprise-Scale Graph Deployments
4 September 2024

This Week in Neo4j: NODES 2024, GraphRAG, Graph Data, Knowledge Graph and more
31 August 2024

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Applying Graph Analytics to Game of Thrones
12 June 2019, Amy Hodler & Mark Needham, Neo4j (guest author)

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

The openCypher Project: Help Shape the SQL for Graphs
22 December 2015, Emil Eifrem (guest author)

show all

Recent citations in the news

GridGain Advances Its Unified Real-Time Data Platform to Help Enterprises Accelerate AI-Driven Data Processing
10 July 2024, insideBIGDATA

GridGain Sponsoring Strategic AI and Kafka Conferences This Month
4 September 2024, Datanami

GridGain in-memory data and generative AI
10 May 2024, Blocks & Files

Data Management News for the Week of July 12; Updates from Cloudera, HerculesAI, Oracle & More
12 July 2024, Solutions Review

GridGain Announces Call for Speakers for Virtual Apache Ignite Summit 2024
8 February 2024, Datanami

provided by Google News

Neo4j lowers barriers to graph technology with gen AI copilot, 15x read capacity
4 September 2024, VentureBeat

Neo4j Transforms Its Cloud Database Portfolio to Accelerate Graph Adoption & GenAI for the Enterprise
4 September 2024, PR Newswire

Neo4j charts upward course for GraphRAG in graph databases
4 September 2024, Techzine Europe

Neo4j Simplifies Graph Database in the Cloud
4 September 2024, Datanami

Neo4j Transforms Its Cloud Database Portfolio to Accelerate Graph Adoption & GenAI for the Enterprise
9 September 2024, insideBIGDATA

provided by Google News

Share this page